Project description:In this study, we performed LC-QTOF-MS-based metabolomics and RNA-seq based transcriptome analysis using seven tissues of M. japonicus.
Project description:Full clinical data for a cohort of 199 individuals with acute coronary syndrome.
Untargeted serum metabolomics using the Metabolon platform for individuals with ACS (n=156).
Serum metabolomics using the Nightingale Health (NMR) platform for individuals with ACS and controls (ACS, n=191; controls, n=961).
Project description:To evoke further attention to the potential hazard of increasingly accumulative blue light exposure, we construct a series of in vivo Drosophila models employed for multi-omics analyses. This project includes the identification results of untargeted metabolome quantification by LC-MS/MS and the Input and m6A IP data of MeRIP-seq of w1118 male adult whole flies.
Project description:The purpose of this study is to identify the characteristics of different HCC subtypes through next generation sequencing and metabolome analysis.The samples for transcriptome sequencing were collected from 60 cases of HCC, 30 of which were also used for whole exome sequencing and LC-MS/MS.
Project description:Colon cancer onset and progression is strongly associated with the presence, absence, or relative abundances of certain microbial taxa in the gastrointestinal tract. However, specific mechanisms affecting disease susceptibility related to complex bacterial mixtures are poorly understood. We used a multi-omics approach to determine how differences in the complex gut microbiome (GM) influence the metabolome and host transcriptome and ultimately affect susceptibility to adenoma development. Fecal samples collected from Pirc rats harboring two distinct complex GMs were analyzed using ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS). We identified putative metabolite profiles that predicted future disease severity from samples collected prior to observable disease onset. Transcriptome analyses performed after disease onset on normal epithelium and tumor tissues suggests that the GM also alters the host transcriptome. Integrated pathway (IP) analyses of the metabolome and transcriptome based on putatively identified metabolic features indicate that bile acid biosynthesis was enriched in rats with high tumors (GM:F344) along with increased fatty acid metabolism and mucin biosynthesis. These data emphasize the utility of using untargeted metabolomics to identify metabolites for revealing signatures of susceptibility and resistance.